Interaction Effects Between Learner Characteristics and Dialogue Format in TTS Dialogue-Based Lessons

A Semi-Automated System for Generating Dialogue-Based TTS Lessons Using Large Language Models: An Exploratory Study of Educational Potential

This study proposes a semi-automated system for generating dialogue-based lessons using Large Language Models (LLMs) and Text-to-Speech (TTS) technology, and exploratorily examines its educational potential via a practical quasi-experiment. The system augments rather than replaces educators through a three-stage human-in-the-loop workflow (LLM-based slide/narration generation, educator review, automated audiovisual integration), and introduces a novel method for generating Expert-Novice dialogue narration based on cognitive apprenticeship theory. In a study of 245 first-year high school students who sequentially experienced three lesson formats (instructor voice, single-speaker TTS, dialogue TTS; content differed across sessions, limiting format/content separation), we conducted within-subject (Friedman test, N<=183) and repeated cross-sectional (Mann-Whitney U, N=229/206) analyses. TTS audio did not substantially degrade the learning experience versus instructor voice, supported by TOST equivalence testing. Dialogue TTS was significantly superior to single TTS in comprehension (p=.006, q=.025) and cognitive engagement (p=.019, q=.048); enjoyment was non-significant after FDR correction (q=.081) but reached significance after controlling for prior knowledge (proportional-odds model, OR=1.65, q=.025), and these advantages were not attributable to prior-knowledge imbalance. Conversely, single TTS was superior in audio naturalness (p<.001, q<.001, r=-.238), revealing a trade-off between dialogue's benefits and higher extraneous cognitive load. Dialogue format was preferred by 66.9% of learners as most enjoyable (p<.001). These results reflect a fixed-order design; replication is needed before generalizing them as effects of lesson format. This study provides a theoretical and empirical basis for the educational acceptability of TTS audio and for TTS lesson-format design.

Teaching Interactional Strategies in an Online L2 Turkish Classroom: A CA-Informed Five-Step Model for Turn-Taking and Floor Management

This study examines how interactional strategies and awareness of spoken language can be introduced, developed, and practiced in a synchronous online Turkish as a second language (TSL) setting through a conversation analysis (CA)-informed pedagogical framework. Employing an action research design, the study implemented iterative instructional cycles with five adult L2 Turkish learners in live Zoom-based classes. Drawing on qualitative data from classroom interaction, learner reflections, and task-based speaking performances, the study proposes and evaluates a five-step teaching model consisting of (1) feedback, (2) preparation and awareness-raising, (3) watching and conversation analysis, (4) in-class speaking tasks, and (5) out-of-class speaking tasks. The findings suggest that this model may support learners’ emerging interactional competence, as reflected in more frequent participation, greater use of discourse markers, and an increased orientation to turn-taking and floor management. Learners also reported heightened awareness of differences between spoken and written Turkish, along with reduced speaking anxiety and enhanced communicative self-confidence. Overall, the study indicates that CA-informed, interaction-focused online instruction may be a productive approach to fostering interactional competence within this cohort when pedagogical design emphasizes sustained, socially situated interaction.

ANALYSIS OF TEACHER-STUDENT INTERACTION IN EFL CLASSROOM

A Study on Teacher-Student Verbal Interaction in Different Types of High School English Classes Based on iFIAS

: This study employs the improved Flanders Interaction Analysis System (iFIAS) to examine teacher-student verbal interaction in different high school English lesson types, specifically a reading-and-thinking lesson and a listening-and-speaking lesson. Through quantitative coding and qualitative analysis of classroom video recordings, the study explores the characteristics of classroom verbal structure, teacher-student questioning patterns, and teaching styles across the two lesson types. The findings reveal that both lessons demonstrate a well-balanced distribution of teacher talk, student talk, classroom silence, and technology use, with student autonomy showing improvement compared to traditional classrooms. The teacher adopts differentiated questioning strategies and teaching styles in response to the distinct instructional objectives and student performance characteristics of each lesson type. This study provides empirical evidence and practical guidance for optimizing teacher-student interaction in secondary English classrooms, suggesting that teachers should create authentic language contexts to encourage student questioning and integrate technology to enhance interaction quality.

Reflective Dialogue or Prompt Refinement? Effects of Tutor Scaffolding on Students' Independent LLM Use for Programming

While Large Language Models (LLMs) can provide personalized support in learning, several studies have raised concerns regarding their use in education. Importantly, learning depends on how students engage with LLMs. This study examined how two types of LLM-based tutors shape students'prompting practices, learning, and subsequent LLM-use: a Socratic-Guidance (SG) tutor, which structures interaction through dialogic questioning, and a Prompt-Refinement (PR) tutor that guides the formulation of effective prompts. We conducted a two-phase study in a graduate-level mobile robotics course: 66 students used either the SG or PR tutor during a 6-week intervention, followed by 52 students using an unconstrained LLM during a 3-week course project. Results show that while the SG- and PR tutors led to similar task performance and prompting patterns during guided use, they differ in learning outcomes and later LLM-use. SG-students, relative to PR-student, achieved higher learning gains in later sessions, and were more likely to adopt understanding-driven prompting strategies, which are predictive of higher understanding, when using an unconstrained LLM. Although learners perceived the SG tutor as less efficient, the findings suggest that Socratic guidance supports the development of students'capacity to learn with LLMs over time, highlighting its importance for LLM tutor design.

Exploring Students' Cognitive Engagement in English Language Classrooms Through Mobile-Assisted Language Learning (MALL)

This study aimed to explore students' cognitive engagement during the learning of Passive Voice through Educaplay's Froggy Jump feature within a Mobile-Assisted Language Learning (MALL) environment. A qualitative case study design was employed involving five Grade XI students and one English teacher at a senior high school in Cirebon, Indonesia. Data were collected through semi-structured interviews, classroom observations, and document analysis, and analyzed using the interactive model of Miles, Huberman, and Saldaña, including data condensation, data display, and conclusion drawing and verification. The findings revealed four interconnected dimensions of cognitive engagement: deep learning strategies, self-regulation, mental effort and persistence, and strategic problem solving. Students actively analyzed grammatical structures, monitored their understanding, sustained cognitive effort despite learning difficulties, and developed strategies to solve Passive Voice tasks collaboratively. The study concludes that gamified MALL fosters meaningful cognitive engagement when supported by teacher scaffolding and peer interaction. These findings imply that English teachers should integrate gamified mobile learning with reflective and collaborative instructional practices to promote deeper grammar learning and higher-order thinking.